Conventional endoscopic procedures typically rely on the use of a flexible fiber optic tube which is inserted in the patient's body to visually examine an inner anatomical structure. The operator can then manipulate the tube inside the anatomical structure to search for any anatomical abnormalities.
Conventional colonoscopies using this procedure, although reliable, are both costly in money and time. Moreover, it is an invasive, uncomfortable and sometimes painful procedure for the patient.
Non-invasive procedures have been used to reduce at least one of the above mentioned drawbacks of the invasive colonoscopic procedure.
These non-invasive procedures use imaging techniques such as a computed tomography (CT) scanning to obtain image data representative of the anatomical structure to analyze. These procedures nevertheless require a cathartic preparation of the patient for colon cleansing prior to the exam.
To even reduce the discomfort felt by the patient, minimum cathartic preparation procedures that tag liquid and solid fecal matter for subsequent virtual removal using digital subtraction algorithms have been proposed.
However, the imaging techniques used to obtain the image data typically present a spatial resolution which generates a blur at each anatomical interface.
Consequently, when removing the tagging material, these algorithms may artificially smooth the surface between the removed material and the colon's inner wall and polyps or other abnormalities present in the colon may be inadvertently removed or wrongly reduced to an acceptable level, which is a major concern.
These algorithms generally rely on image segmentation by using a threshold adapted for characterizing the interfaces of the structure under analysis.
However, since the different anatomical structures may be very different from each other, a simple threshold may not allow to conveniently segment a structure in a single pass. Indeed, soft tissues, bones and fat tissues have different densities.
In order to take into consideration this great variability of the structures, different techniques have been used. For example, PCT international applications published under publication numbers WO2008/089492, WO2007/064980 and WO02/029764 and US patent applications published under publication numbers 2008/0118133 and 2008/0008367 teach various methods for electronic cleansing of medical images. However, they still use a threshold for structure segmentation and the resulting segmentation may still remain approximated for a plurality of unitary image elements. The interfaces between the different structures may then still be smoothed. This may lead an operator to a wrong diagnosis, which is a major issue.
U.S. Pat. No. 6,366,800 describes a method for automatic analysis in virtual endoscopy. This method however also relies on segmentation techniques and the resulting segmentation may still remain approximated.
It would therefore be desirable to provide an improved method for electronic cleansing of medical images that will reduce at least one of the above-mentioned drawbacks.